The growth of minimally invasive therapies has led to a growing interest in the potential for computer-based simulation for training. Many computer-based medical simulators have been designed to teach these new techniques. Most of these efforts have focused on laparoscopic surgery, in which rigid tools are inserted into the patient's abdomen and visual feedback is provided by an endoscopic camera that produces a high-definition color image. These simulators are predominantly skills trainers, emphasizing the two-dimensional hand-eye coordination practice that is useful for laparoscopic surgery.
Interventional cardiology shares characteristics with other minimally invasive therapies that make it suitable for simulator-based learning: it requires complex understanding of three-dimensional anatomy from two-dimensional displays and fine hand-eye coordination. As with surgery, complications from improperly performed cardiac catheterization can have catastrophic results. Thus, there is a strong need for simulator based training before an actual procedure is attempted.
However, interventional cardiology simulation presents unique challenges. First, visual feedback is not provided by visible light but by fluoroscopy, which must be simulated in real time while allowing for changes in points of view as the fluoroscope moves around the patient. Second, the catheters, guide wires, and stents are flexible devices and therefore must be modeled as deformable objects, which is not the case for rigid laparoscopic tools. To control the motion of a catheter or guide wire within the vascular network, the physician can only push, pull or twist the proximal end of the device. Since such devices are constrained inside the patient's vasculature, it is the combination of input forces and contact forces that allow them to be moved toward a target.
The main characteristics of wire-like structures or flexible objects or segmented objects that simulation models attempt to capture include geometric non-linearities, high tensile strength and low resistance to bending. However, many known flexible object simulation models are not suitable for real-time applications.
Known models for flexible objects used in the context of medical simulation include articulated body methods (“ABM”), which represent the object as a set of rigid segments connected by rotary and torsional springs (see, e.g., Dawson et al., “Designing a Computer-Based Simulator for Interventional Cardiology Training”, Catheterization and Cardiovascular Interventions 51:522-527 (2000)). However, since these methods use explicit integration, they do not provide the necessary stiffness and speed as required by many applications. In addition, stability is affected by the length of the smallest segment.
Other known models for flexible objects use beam finite elements (see, e.g., Cotin et. al., “New Approaches to Catheter Navigation for Interventional Radiology Simulation”, MICCAI (2005)). However, these methods exhibit problems similar to the articulated body method, due to using explicit integration and iterative solution techniques.
Further, many non-invasive procedures use multiple coaxial tools, such as a wire sliding inside a catheter. Some procedures use three or more coaxial tools. These tools not only interact with a patient's vascular system or other internal barriers, but interact with each other in their coupled state. The interaction with each other greatly complicates a simulation of multiple tools, requiring much more complex calculations.
Prior solutions for simulating coupled objects use external forces and explicit integration methods. The problem with these approaches is that either the coupling is not enforced strictly enough, resulting in noticeable interpenetrations between the objects, or the coupled system exhibits unstable behavior. Other known solutions augment a system matrix to enforce strict coupling (see Cotin et al., “Real-Time Elastic Deformations of Soft Tissues for Surgery Simulation”, TVCG 1998 and Lindblad, “Real-time Finite Element Based Virtual Tissue Cutting”, MMVR 2006). However, known augmented systems require computationally demanding numerical algorithms, which may prevent their application in real-time simulation applications. Another known coupling method enforces constraints during collision detection (see Baraff et al., “Large Steps in Cloth Simulation”, SIGGRAPH 1998). However, this method is limited to handling unilateral surface contact for self-collision detection and works for a single object only.
Based on the foregoing, there is a need for an improved system and method for simulating coupled tools or other segmented objects.